Experimentation is useful for testing new or different ideas, and can lead to better products, methods, techniques, etc. During experimentation, a number of alternate ideas or approaches may be provided to various test subjects and the results observed. For example, experiments can be set-up for testing various structures or arrangements for content (e.g., data or information which can be presented to a person in some form or fashion). To maximize the benefit of experimentation, it is desirable to have a suitable population of test subjects. In general, the greater the number of alternate ideas, the greater the number of test subjects required in order to provide or obtain accurate test results for an experiment. As can be imagined, for experiments involving many alternate ideas, the administration of the experiments can be quite burdensome, especially if the administrative tasks (e.g., distributing embodiments for alternate ideas, collecting information observed during the experiments, and analyzing the collected information) are performed manually. Previously developed techniques for experimentation have suffered from these and other problems.